Automatic diagnosis and location of open-switch fault in brushless DC motor drives using wavelets and neuro-fuzzy systems

The faulty performance of permanent-magnet (PM) brushless dc motor drives is studied under open-switch conditions. The wavelet transform is used to extract diagnostic indices from the current waveform of the motor dc link. An intelligent agent based on adaptive neuro-fuzzy inference systems (ANFIS) is developed to automate the fault identification and location process. ANFIS is trained offline using simulation results under various healthy and faulty conditions obtained from a lumped-parameter, network model. ANFIS testing shows that the system could not only detect the open-switch fault, but also identify the faulty switch. Good agreement between simulation results and measured waveforms confirms the effectiveness of the proposed methodology.     

A DC linear motor with a square armature

One of the advantages in using DC linear motors for low speed linear drives is that the position and speed of these motors can be precisely controlled with the help of a feedback circuit. In addition, linear motors get rid of the rotary-to-linear conversion mechanism, hence reduce the weight cost backlash and dynamic complexity which produces friction, and eventually minimizes the space required by the drive. The neodymium-iron-boron (NdFeB) permanent magnet with high energy product has been used as the field source of these motors thus reducing the size and weight of the motors further. This paper describes the analysis of flux and force in a DC linear stepping motor built with NdFeB magnets. In order to verify the experimental results obtained for determining the performance of the motor, a computational method has been employed to compute the flux distributions throughout the machine. The discrepancy between the measured and computed values of axial and radial flux at most points ranges between 8% and 16% while the discrepancy between the measured and computed values of starting thrust is in the range between 4% and 13%     

Laboratory implementation of a neural network trajectory controllerfor a DC motor

The laboratory implementation of a neural network controller for high performance DC drives is described. The objective is to control the rotor speed and/or position to follow an arbitrarily selected trajectory at all times. The control strategy is based on indirect model reference adaptive control (MRAC). The motor characteristics are explicitly identified through a multilayer perceptron type neural network. The output of the trained neural network is used to drive the motor in order to achieve a desired time trajectory of the controlled variable. The neural network controller is assembled in a commercially available PC-based real-time control system shell, using software subroutines. An H-bridge, DC/DC voltage converter is interfaced with the computer to generate the specified terminal voltage sequences for driving the motor. All software and hardware components are off the shelf. The versatility of the motor/controller arrangement is displayed through real-time plots of the controlled states     

Identification and control of a DC motor using back-propagationneural networks

An artificial-neural-network (ANN)-based high-performance speed-control system for a DC motor is introduced. The rotor speed of the DC motor can be made to follow an arbitrarily selected trajectory. The purpose is to achieve accurate trajectory control of the speed, especially when motor and load parameters are unknown. The unknown nonlinear dynamics of the motor and the load are captured by the ANN. The trained neural-network identifier is combined with a desired reference model to achieve trajectory control of speed. The performances of the identification and control algorithms are evaluated by simulating them on a typical DC motor model. It is shown that a DC motor can be successfully controlled using an ANN     

改善直流牵引电机换向性能探讨

介绍了衡量直流电机换向性能的指标参数;分析了如何根据无火花换向区域试验结果,通过调整电机的参数,使电机达到最佳换向;介绍了在电机设计时改善电机换向的几种有效方法。     

Design and demonstration of a microcomputer controller for anindustrial sized DC motor

A method of designing a three-phase fully-controlled thyristor-DC motor drive system with speed and/or current closed-loop control is presented. Both the circuit design and the control algorithm of a continuous (analog) controller or a digital controller design are studied. The effectiveness of the design method is well verified by extensive experiments. The dynamics of the system reasonably confirm the theoretical analysis. In addition, the goal of multiple operating modes of the thyristor converter is also achieved. It is shown that both good performance and good flexibility with online calculation can be obtained by using a low-cost microcomputer. The parts cost of the microcomputer-based controller is still a little higher than the continuous controller, but the trend is towards lower costs of microcomputers. The main advantages of the digital controller are its versatility and flexibility     

防止直流牵引电动机环火的措施

在对直流牵引电动机环火产生的原因进行分析的基础上,提出了防止环火的各项措施。     

Control of a linear permanent magnet brushless DC motor via exactlinearization methods

The author develops a position controller for permanent magnet brushless DC motors (PMBDCMs) which systematically determines control laws for operation in both the transient and steady-state with consideration of reluctance force. The controller design is based on a differential geometric approach which assists the motor in overcoming its inherent deficiencies, such as effects of torque ripples and reluctance torque. This is achieved by transforming the nonlinear state equations into an exact linear model. Computer simulations of the resulting closed-loop system were performed to demonstrate the effectiveness of the proposed control laws. Simulation results of the control variables were injected into the actual nonlinear system in an experimental open-loop setup to validate the design procedure     

Performance analysis of a PV powered DC motor driving a 3-phaseself-excited induction generator

Photovoltaic (PV) powered DC motors driving dedicated loads (e.g. water pumps) are increasingly used in the remote rural areas of many developing countries. The key to their success is simplicity (direct coupling, no DC-AC inversion, no storage batteries, etc.). In this paper, a PV powered DC motor is used to drive an isolated three-phase self-excited induction generator (SEIG). It is found that due to the unique torque-speed characteristics of the SEIG, utilization efficiency is close to maximum at all insolation levels with no peak-power tracking. The proposed arrangement is useful as part of an integrated renewable energy system (IRES), which takes advantage of the inherent diversity of wind and insolation in most developing countries to improve power quality. The SEIG is driven by wind turbine, DC motor, or both. Performance of the system under different insolation conditions is analyzed     

Matching of a DC motor to a photovoltaic generator using a step-upconverter with a current-locked loop

A photovoltaic (PV) generator is a nonlinear device having insolation-dependent volt-ampere characteristics. Because of its relatively high cost, the system designer is interested in optimum matching of the motor and its mechanical load to the PV generator so that maximum power is obtained during the entire operating period. However, since the maximum-power point varies with solar insolation, it is difficult to achieve an optimum matching that is valid for all insolation levels. In this paper it is shown that for maximum power, the generator current must be directly proportional to insolation. This remarkable property is utilized to achieve insolation-independent optimum matching. A shunt DC motor driving a centrifugal water pump is supplied from a PV generator via a step-up converter whose duty ratio is controlled using a current-locked feedback loop     

Mechanical fault detection in a medium-sized induction motor using stator current monitoring

This paper presents the results of an experimental study of the detection of mechanical faults in an induction motor. As is reasonably well known, by means of analysis of combinations of permeance and magneto-motive force (MMF) harmonics, it is possible to predict the frequency of air gap flux density harmonics which occur as a result of certain irregularities in an induction motor. In turn, analysis of flux density harmonics allows the prediction of induced voltages and currents in the stator windings. Reviewing this theory, equations which may aid in the identification of mechanical faults are presented. These equations include both those which indicate eccentric conditions and those which have been suggested to help identify bearing faults. The development of test facility to create eccentricity faults and bearing fault conditions is described. This test facility allows rapid access to the motor bearings, allowing an investigation into the ability to detect faulted bearing conditions using stator current monitoring. Experimental test results are presented, indicating that it may be possible to detect bearing degradation using relatively simple and inexpensive equipment.     

Numerical investigation and optimization of the thermal performance of a brushless DC motor

A computational study of a brushless DC motor is presented to determine the thermo-flow characteristics in the windings and bearings under the effects of heat generation. The rotation of the rotor blades drives an influx of ambient air into the rotor inlet. The predicted inflow rates were higher at the front inlet than at the rear inlet due to non-uniform pressure distribution. A recirculation zone appeared in the tiny interfaces between windings. The poor cooling performance was caused by flow separation near the groove threshold by the inclination angle of the bearing groove and by a relatively slow velocity near the bearing and between windings. Based on these results, design parameters for the inlet location and geometry, and for the bearing groove geometry, were determined and optimized to enhance the cooling performance up to 24%.     

牵引电机环火故障电子检测装置

采用传感技术,实时采集内燃机车牵引电机换向器火花特征参数,运用单片机进行信息处理和自动控制,有效防止牵引电机环火故障的发生。     

Torque ripple analysis of a PM brushless DC motor using finite element method

Three-phase permanent magnet brushless DC motors are widely used. As a function of the rotor position, the torque produced by these machines has a pulsating component in addition to the DC component. This pulsating torque has a fundamental frequency corresponding to six pulses per electrical revolution of the motor. The shape of the torque waveform and, thus, the frequency content of the waveform can be influenced by several factors in the motor design and construction. This paper addresses the various factors that influence the torque waveshape. It is shown that in addition to the basic induced electromotive force (EMF) waveshape, the magnetic saturation in the stator core, and the accuracy in the skewing are also key factors in determining the torque waveshape. Computer simulation using finite element technique has been conducted to study the torque waveform. Simulation results successfully duplicated the torque waveforms measured in experiments under different excitation currents.     

Operating modes of the brushless DC motor with a 120° inverter

An analysis of the brushless DC motor with a 120° inverter is presented. It is shown that the brushless DC motor-120° inverter system has several distinct operating modes. The status of the motor phase current in which the inverter transistors are not conducting (gated off) is used to classify the modes of operation. These modes are identified and their relationship to the speed and the advance in the firing angle is established     

Variable structure tracking of DC motor for high performanceapplications

The authors present a novel application of variable structure system control (VSS) for online tracking of DC motors. By the proposed technique, the rotor position, speed, and current can follow preselected tracks (a track is a time history selected in advance). The theory of the VSS is modified to include the tracking option for the general case of the multi-input/multi-output system. The robustness of the proposed tracking controller is ensured at all times. By selecting the tracks as proposed here, the electrical and mechanical stresses on the motor are substantially reduced, and soft starting of the motor is achieved. The entire drive system was built and tested in the laboratory by using off-the-shelf components and software. The test results show the effectiveness of the proposed tracking controller in high-performance drive applications such as robotics, manipulation, and actuation     

Analysis of optimum matching of a DC series motor driven centrifugal pump to a photovoltaic generator

Direct coupling between a photovoltaic (PV) generator and a monoblock DC series motor connected with ventilator load torque centrifugal pump has been analyzed theoretically as a function of the no flow motor-pump speed (w₀) and the water head of the pump. The value of w₀ is directly related with motor terminal voltage which has been derived. The condition of the maximum motor-pump efficiency has been deduced mathematically in terms of the speed-torque constant K₁ at a given w₀ for different water heads. The variation of w₀ and perfectly matched motor constant (M₀) have been calculated at various solar insolation and different water heads. From these theoretical studies, the optimum matching condition has been suggested according to the requirements. One optimally matched monoblock DC series motor and centrifugal pump, of 125 W, was chosen for study. The calculated coupling efficiencies such as electrical energy, mechanical energy, and hydraulic energy of the pump, have been discussed. Some of these results are also compared to information available in the literature.     

A robust control method for a PV-supplied DC motor using universal learning networks

In this paper, a new robust control method and its application to a photovoltaic (PV) supplied, separately excited DC motor loaded with a constant torque is discussed. The robust controller is designed against the load torque changes by using the first and second ordered derivatives of the universal learning networks (ULNs). These derivatives are calculated using the forward propagation algorithm, which is considered as an extended version of real time recurrent learning (RTRL). In this application, two ULNs are used: The first is the ULN identifier trained offline to emulate the dynamic performance of the DC motor system. The second is the ULN controller, which is trained online not only to make the motor speed follow a selected reference signal, but also to make the overall system operate at the maximum power point of the PV source. To investigate the effectiveness of the proposed robust control method, the simulation is carried out at four different values of the robustness coefficient γ in two different stages: The training stage, in which the simulation is done for a constant load torque. And the control stage, in which the controller performance is obtained when the load torque is changed. The simulation results showed that the robustness of the control system is improved although the motor load torque at the control stage is different from that at the training stage.     

柴油机故障诊断与分析

通过采集16V240ZJ型柴油机振动信号并利用小波包分解对振动信号进行消噪处理,利用频带分解技术提取振动信号的特征值向量,应用神经网络实现柴油机自适应的故障诊断。     

基于模糊神经网络的凝汽器故障诊断系统

凝汽器是凝汽式汽轮机的主要辅助设备之一,凝汽器系统运行中出现的故障与故障征兆之间是非线性关系,具有复杂性、模糊性和随机性,难以用数学公式表示.针对此情况,结合模糊理论与神经网络两种故障诊断方法的优势,建立凝汽器故障诊断专家系统.系统采用模糊隶属度函数表示难以准确描述的领域专家知识,采用神经网络进行推理,使诊断结果具有较高的可靠性.